The major lightning regions and associated casualties over India

Natural Hazards - Lightning, a climate-related highly localized natural phenomenon, claims lives and damage properties. These losses could only be reduced by the identification of active seasons...     

Chemical characterization of water-soluble aerosols in different residential environments of semi aridregion of India

This paper deals with the atmospheric concentrations of PM₅ and PM_2.5 particulate matter and its water soluble constituents along with the size distribution of ions and spatial variation at three different residential environments in a semiarid region in India. Samples were collected from the indoors and outdoors of urban, rural and roadside sites of Agra during October 2007–March 2008. The mean concentrations of PM_2.5 indoors and outdoors were 178 μgm⁻³ and 195 μgm⁻³ while the mean concentrations of PM₅ indoors and outdoors were 231.8 μgm⁻³ and 265.2 μgm⁻³ respectively. Out of the total aerosol mass, water soluble constituents contributed an average of 80% (33% anions, 50% cations) in PM₅ and 70% (29% anions, 43% cations) in PM_2.5. The indoor–outdoor ratio of water soluble components suggested additional aerosol indoor sources at rural and roadside sites. Indoor–outdoor correlations were also determined which show poor relationships among concentrations of aerosol ions at all three sites. Univariate Pearson correlation coefficients among water soluble aerosols were determined to evaluate the relationship between aerosol ions in indoor and outdoor air.     

Hydro-climatological changes in the Colorado River Basin over a century

This study evaluates changes in streamflow, temperature and precipitation over a time span of 105 years (1906–2010) in the Colorado River Basin (CRB). Monthly precipitation and temperature data for 29 climate divisions, and streamflow data for 29 naturalized gauges were analyzed. Two variations of the Mann-Kendall test, considering lag-1 auto correlation and long-term persistence, and the Pettitt test were employed to assess trends and shifts, respectively. Results indicated that streamflow increased during the winter–spring months and decreased during the summer– autumn period. Decreasing trends in winter precipitation were identified over snow-dominated regions in the upper basin. Significant increases in temperature were detected over several months. Major shifts were noticed in 1964, 1968 and in the late 1920s. Increasing temperature while decreasing streamflow and precipitation were noticed after major shifts in the 1930s, and these shifts coincided with coupled phases of El Niño Southern Oscillation and Pacific Decadal Oscillation.

EDITOR A. Castellarin; ASSOCIATE EDITOR R. Hirsch     

Optimal allocation of water and land resources for maximizing the farm income and minimizing the irrigation-induced environmental problems

The continuous decrease in good quality water and land resources and concurrent increase in global population accentuates the need of optimal allocation of these resources to fulfilling the rising food requirements. This study presents the formulation and application a management model for the optimal allocation of available good quality water and land resources to maximize the farm revenue of a canal command area. A groundwater balance constraint was imposed on the model, which moderates the irrigation-induced environmental problems of waterlogging and salinization, while making the optimal allocation of resources. The model results show a reduction in mustard, rice, and gram crop areas against an increase in sorghum, millets, and wheat areas. The net annual revenue from the command area increased by about 18 % under the optimal allocation plans. The farmers and stakeholders concerned in the actual agricultural production process are suggested to use groundwater and canal water conjunctively to maximizing the farm income. This strategy would also mitigate the hydrological imbalances to the groundwater system without installing costly drainage systems which is not viable as the quality of groundwater is poor and drainage water may cause a serious disposal problem. The developed model can be used as a reliable decision tool for taking the farm and regional level decisions of optimal land and water resources allocation and is able to solve the irrigation-induced environmental problems of agricultural systems.     

Effect of Monetary Incentives on Mail Survey Response Rates for Midwestern Farmers

Response rates to mail-based surveys have declined in recent decades, and survey response rates for farmers tend to be low overall. Maintaining high response rates is necessary to prevent non-response bias. Historically, incentives have been an effective tool to increase response rates with general populations. However, the effect of incentives on farmers has not been well tested. In this study, we experimentally manipulated the use of a $2 incentive in two surveys targeted at farmers. We tested both the use of the incentive and the timing of incentive distribution in the survey process. We found the incentive significantly increased response rates with farmers but there was no significant effect of when the incentive was distributed. Additionally, we evaluated the cost-effectiveness of using the incentive. While the incentive increased response rate, the cost per survey response also increased and the cost of the incentive was not offset by the increased response rate.     

Using large‐scale climatic patterns for improving long lead time streamflow forecasts for Gunnison and San Juan River Basins

In a water‐stressed region, such as the western United States, it is essential to have long lead times for streamflow forecasts used in reservoir operations and water resources management. Current water supply forecasts provide a 3‐month to 6‐month lead time, depending on the time of year. However, there is a growing demand from stakeholders to have forecasts that run lead times of 1 year or more. In this study, a data‐driven model, the support vector machine (SVM) based on the statistical learning theory, was used to predict annual streamflow volume with a 1‐year lead time. Annual average oceanic–atmospheric indices consisting of the Pacific decadal oscillation, North Atlantic oscillation (NAO), Atlantic multidecadal oscillation, El Niño southern oscillation (ENSO), and a new sea surface temperature (SST) data set for the ‘Hondo’ region for the period of 1906–2006 were used to generate annual streamflow volumes for multiple sites in the Gunnison River Basin and San Juan River Basin, both located in the Upper Colorado River Basin. Based on the performance measures, the model showed very good forecasts, and the forecasts were in good agreement with measured streamflow volumes. Inclusion of SST information from the Hondo region improved the model's forecasting ability; in addition, the combination of NAO and Hondo region SST data resulted in the best streamflow forecasts for a 1‐year lead time. The results of the SVM model were found to be better than the feed‐forward, back propagation artificial neural network and multiple linear regression. The results from this study have the potential of providing useful information for the planning and management of water resources within these basins. Copyright © 2012 John Wiley & Sons, Ltd.     

Rapid flash flood calamity in Chamoli,Uttarakhand region during Feb 2021: an analysis based on satellite data

Natural Hazards - The present study investigates the accelerating factors for extreme flash flood at Chamoli district of Uttarakhand on 7 February 2021. The Sentinel-2A and 2B satellite data have...